Accessing dict keys like an attribute?

Question

I find it more conveniant to access dict keys as obj.foo instead of obj['foo'], so I wrote this snippet:

class AttributeDict(dict):
    def __getattr__(self, attr):
        return self[attr]
    def __setattr__(self, attr, value):
        self[attr] = value

However, I assume there must be some reason that Python doesn't provide this functionality out of the box. What would be the caveats and pitfalls of accessing dict keys in this manner?

Answer 1

How about Prodict, the little Python class that I wrote to rule them all:)

Plus, you get auto code completion, recursive object instantiations and auto type conversion!

You can do exactly what you asked for:

p = Prodict()
p.foo = 1
p.bar = "baz"

Example 1: Type hinting

class Country(Prodict):
    name: str
    population: int

turkey = Country()
turkey.name = 'Turkey'
turkey.population = 79814871

Example 2: Auto type conversion

germany = Country(name='Germany', population='82175700', flag_colors=['black', 'red', 'yellow'])

print(germany.population)  # 82175700
print(type(germany.population))  # <class 'int'>

print(germany.flag_colors)  # ['black', 'red', 'yellow']
print(type(germany.flag_colors))  # <class 'list'>

Answer 2

This isn't a 'good' answer, but I thought this was nifty (it doesn't handle nested dicts in current form). Simply wrap your dict in a function:

def make_funcdict(d={}, **kwargs)
    def funcdict(d={}, **kwargs):
        funcdict.__dict__.update(d)
        funcdict.__dict__.update(kwargs)
        return funcdict.__dict__
    funcdict(d, **kwargs)
    return funcdict

Now you have slightly different syntax. To acces the dict items as attributes do f.key. To access the dict items (and other dict methods) in the usual manner do f()['key'] and we can conveniently update the dict by calling f with keyword arguments and/or a dictionary

Example

d = {'name':'Henry', 'age':31}
d = make_funcdict(d)
>>> for key in d():
...     print key
... 
age
name
>>> print d.name
... Henry
>>> print d.age
... 31
>>> d({'Height':'5-11'}, Job='Carpenter')
... {'age': 31, 'name': 'Henry', 'Job': 'Carpenter', 'Height': '5-11'}

And there it is. I'll be happy if anyone suggests benefits and drawbacks of this method.

Answer 3

class AttrDict(dict):

     def __init__(self):
           self.__dict__ = self

if __name__ == '____main__':

     d = AttrDict()
     d['ray'] = 'hope'
     d.sun = 'shine'  >>> Now we can use this . notation
     print d['ray']
     print d.sun

Answer 4

What would be the caveats and pitfalls of accessing dict keys in this manner?

As @Henry suggests, one reason dotted-access may not be used in dicts is that it limits dict key names to python-valid variables, thereby restricting all possible names.

The following are examples on why dotted-access would not be helpful in general, given a dict, d:

Validity

The following attributes would be invalid in Python:

d.1_foo                           # enumerated names
d./bar                            # path names
d.21.7, d.12:30                   # decimals, time
d.""                              # empty strings
d.john doe, d.denny's             # spaces, misc punctuation 
d.3 * x                           # expressions  

Style

PEP8 conventions would impose a soft constraint on attribute naming:

A. Reserved keyword (or builtin function) names:

d.in
d.False, d.True
d.max, d.min
d.sum
d.id

If a function argument's name clashes with a reserved keyword, it is generally better to append a single trailing underscore ...

B. The case rule on methods and variable names:

Variable names follow the same convention as function names.

d.Firstname
d.Country

Use the function naming rules: lowercase with words separated by underscores as necessary to improve readability.

---

Sometimes these concerns are raised in libraries like pandas, which permits dotted-access of DataFrame columns by name. The default mechanism to resolve naming restrictions is also array-notation - a string within brackets.

If these constraints do not apply to your use case, there are several options on dotted-access data structures.

Answer 5

Just to add some variety to the answer, sci-kit learn has this implemented as a Bunch:

class Bunch(dict):                                                              
    """ Scikit Learn's container object                                         

    Dictionary-like object that exposes its keys as attributes.                 
    >>> b = Bunch(a=1, b=2)                                                     
    >>> b['b']                                                                  
    2                                                                           
    >>> b.b                                                                     
    2                                                                           
    >>> b.c = 6                                                                 
    >>> b['c']                                                                  
    6                                                                           
    """                                                                         

    def __init__(self, **kwargs):                                               
        super(Bunch, self).__init__(kwargs)                                     

    def __setattr__(self, key, value):                                          
        self[key] = value                                                       

    def __dir__(self):                                                          
        return self.keys()                                                      

    def __getattr__(self, key):                                                 
        try:                                                                    
            return self[key]                                                    
        except KeyError:                                                        
            raise AttributeError(key)                                           

    def __setstate__(self, state):                                              
        pass                       

All you need is to get the setattr and getattr methods - the getattr checks for dict keys and the moves on to checking for actual attributes. The setstaet is a fix for fix for pickling/unpickling "bunches" - if inerested check https://github.com/scikit-learn/scikit-learn/issues/6196